Transportation routing systems increasingly use tracking technologies to determine the location and routes traveled by vehicles and computing devices carried by such vehicles. For instance, conventional transportation routing systems use computing devices that employ Global Positioning System (“GPS”) to determine traffic patterns, driver habits, or digital maps of a road network. Tracking devices that use GPS can often improve or provide the data for determining vehicles' locations, routes, and patterns.
Despite improving route detection, conventional GPS-based routing systems sometimes generate or receive inaccurate GPS data. For instance, conventional GPS-based routing systems often generate or receive noisy GPS data indicating incorrect locations of a computing device along a route. Such GPS data may indicate locations within a route that would require a vehicle to accelerate or travel at magnitudes that the vehicle could not exhibit based on standard driving patterns or the laws of physics. For example, noisy GPS data sometimes indicates a vehicle rapidly changing from one latitudinal or longitudinal location to another such location, such as at an intersection with a traffic light. Several factors may cause noisy GPS data, such as a faulty GPS device, the landscape of the area in which a computing device is located, or the speed at which the computing device travels. Accordingly, conventional GPS-based routing systems sometimes inaccurately determine a vehicle's location or route based on noisy GPS data.
To correct for the inaccuracies of GPS data, some conventional map-match routing systems adjust GPS data to predict a vehicle's location within roads of a digital map. For instance, some conventional map-match routing systems use GPS data from a computing device to estimate locations along roads of a digital map. But conventional map-match routing systems require up-to-date maps, among other things, to accurately determine a vehicle's location and routes traveled. Developing such digital maps often requires collecting satellite imagery, managing a mapping fleet of vehicles, and purchasing large amounts of traffic data.
Notwithstanding the expense and difficulty of creating digital maps, conventional map-match routing systems often inaccurately determine the location and routes of vehicles. For example, conventional map-match routing systems sometimes determine a vehicle is located on a non-existent (or incorrect) road based on (i) algorithms that inaccurately match GPS data to roads or (ii) faulty digital maps. After construction of a new road, for example, conventional map-match routing systems may take months (or more) to identify the new road and update the map using a minimum number of observed-data points and an offline process for adjusting the map.
Both conventional GPS-based routing systems and conventional map-match routing systems pose significant technical limitations for on-demand service matching systems that provide transportation vehicles to requestors. On-demand service matching systems often need to accurately determine a location and route of a vehicle in real time (or near real time) to match transportation vehicles with requestors and to accurately determine prices for transport. The inaccuracy and slow adjustment mechanisms of conventional GPS-based routing systems and conventional map-match routing systems inhibit such on-demand service matching systems from determining locations, distances, and/or routes for transport.